[Python-checkins] CVS: python/dist/src/Doc/lib librandom.tex,1.15,1.16
Fred L. Drake
fdrake@users.sourceforge.net
Mon, 22 Jan 2001 10:18:33 -0800
Update of /cvsroot/python/python/dist/src/Doc/lib
In directory usw-pr-cvs1:/tmp/cvs-serv24636/lib
Modified Files:
librandom.tex
Log Message:
Clean up the docs for the "random" module according to comments from Tim
Peters.
This closes SF bug #125919.
Index: librandom.tex
===================================================================
RCS file: /cvsroot/python/python/dist/src/Doc/lib/librandom.tex,v
retrieving revision 1.15
retrieving revision 1.16
diff -C2 -r1.15 -r1.16
*** librandom.tex 2000/12/15 19:07:17 1.15
--- librandom.tex 2001/01/22 18:18:30 1.16
***************
*** 14,22 ****
! The \module{random} module supports the \emph{Random Number
! Generator} interface, described in section \ref{rng-objects}. This
! interface of the module, as well as the distribution-specific
! functions described below, all use the pseudo-random generator
! provided by the \refmodule{whrandom} module.
--- 14,44 ----
! \begin{funcdesc}{choice}{seq}
! Chooses a random element from the non-empty sequence \var{seq} and
! returns it.
! \end{funcdesc}
!
! \begin{funcdesc}{randint}{a, b}
! \deprecated{2.0}{Use \function{randrange()} instead.}
! Returns a random integer \var{N} such that
! \code{\var{a} <= \var{N} <= \var{b}}.
! \end{funcdesc}
!
! \begin{funcdesc}{random}{}
! Returns the next random floating point number in the range [0.0,
! 1.0).
! \end{funcdesc}
!
! \begin{funcdesc}{randrange}{\optional{start,} stop\optional{, step}}
! Return a randomly selected element from \code{range(\var{start},
! \var{stop}, \var{step})}. This is equivalent to
! \code{choice(range(\var{start}, \var{stop}, \var{step}))}.
! \versionadded{1.5.2}
! \end{funcdesc}
!
! \begin{funcdesc}{uniform}{a, b}
! Returns a random real number \var{N} such that
! \code{\var{a} <= \var{N} < \var{b}}.
! \end{funcdesc}
***************
*** 25,90 ****
corresponding variables in the distribution's equation, as used in
common mathematical practice; most of these equations can be found in
! any statistics text. These are expected to become part of the Random
! Number Generator interface in a future release.
\begin{funcdesc}{betavariate}{alpha, beta}
! Beta distribution. Conditions on the parameters are
! \code{\var{alpha} > -1} and \code{\var{beta} > -1}.
! Returned values range between 0 and 1.
\end{funcdesc}
\begin{funcdesc}{cunifvariate}{mean, arc}
! Circular uniform distribution. \var{mean} is the mean angle, and
! \var{arc} is the range of the distribution, centered around the mean
! angle. Both values must be expressed in radians, and can range
! between 0 and \emph{pi}. Returned values will range between
! \code{\var{mean} - \var{arc}/2} and \code{\var{mean} + \var{arc}/2}.
\end{funcdesc}
\begin{funcdesc}{expovariate}{lambd}
! Exponential distribution. \var{lambd} is 1.0 divided by the desired
! mean. (The parameter would be called ``lambda'', but that is a
! reserved word in Python.) Returned values will range from 0 to
! positive infinity.
\end{funcdesc}
\begin{funcdesc}{gamma}{alpha, beta}
! Gamma distribution. (\emph{Not} the gamma function!) Conditions on
! the parameters are \code{\var{alpha} > -1} and \code{\var{beta} > 0}.
\end{funcdesc}
\begin{funcdesc}{gauss}{mu, sigma}
! Gaussian distribution. \var{mu} is the mean, and \var{sigma} is the
! standard deviation. This is slightly faster than the
! \function{normalvariate()} function defined below.
\end{funcdesc}
\begin{funcdesc}{lognormvariate}{mu, sigma}
! Log normal distribution. If you take the natural logarithm of this
! distribution, you'll get a normal distribution with mean \var{mu} and
! standard deviation \var{sigma}. \var{mu} can have any value, and
! \var{sigma} must be greater than zero.
\end{funcdesc}
\begin{funcdesc}{normalvariate}{mu, sigma}
! Normal distribution. \var{mu} is the mean, and \var{sigma} is the
! standard deviation.
\end{funcdesc}
\begin{funcdesc}{vonmisesvariate}{mu, kappa}
! \var{mu} is the mean angle, expressed in radians between 0 and 2*\emph{pi},
! and \var{kappa} is the concentration parameter, which must be greater
! than or equal to zero. If \var{kappa} is equal to zero, this
! distribution reduces to a uniform random angle over the range 0 to
! 2*\emph{pi}.
\end{funcdesc}
\begin{funcdesc}{paretovariate}{alpha}
! Pareto distribution. \var{alpha} is the shape parameter.
\end{funcdesc}
\begin{funcdesc}{weibullvariate}{alpha, beta}
! Weibull distribution. \var{alpha} is the scale parameter and
! \var{beta} is the shape parameter.
\end{funcdesc}
--- 47,113 ----
corresponding variables in the distribution's equation, as used in
common mathematical practice; most of these equations can be found in
! any statistics text.
+
\begin{funcdesc}{betavariate}{alpha, beta}
! Beta distribution. Conditions on the parameters are
! \code{\var{alpha} > -1} and \code{\var{beta} > -1}.
! Returned values range between 0 and 1.
\end{funcdesc}
\begin{funcdesc}{cunifvariate}{mean, arc}
! Circular uniform distribution. \var{mean} is the mean angle, and
! \var{arc} is the range of the distribution, centered around the mean
! angle. Both values must be expressed in radians, and can range
! between 0 and \emph{pi}. Returned values will range between
! \code{\var{mean} - \var{arc}/2} and \code{\var{mean} +
! \var{arc}/2}.
\end{funcdesc}
\begin{funcdesc}{expovariate}{lambd}
! Exponential distribution. \var{lambd} is 1.0 divided by the desired
! mean. (The parameter would be called ``lambda'', but that is a
! reserved word in Python.) Returned values will range from 0 to
! positive infinity.
\end{funcdesc}
\begin{funcdesc}{gamma}{alpha, beta}
! Gamma distribution. (\emph{Not} the gamma function!) Conditions on
! the parameters are \code{\var{alpha} > -1} and \code{\var{beta} > 0}.
\end{funcdesc}
\begin{funcdesc}{gauss}{mu, sigma}
! Gaussian distribution. \var{mu} is the mean, and \var{sigma} is the
! standard deviation. This is slightly faster than the
! \function{normalvariate()} function defined below.
\end{funcdesc}
\begin{funcdesc}{lognormvariate}{mu, sigma}
! Log normal distribution. If you take the natural logarithm of this
! distribution, you'll get a normal distribution with mean \var{mu}
! and standard deviation \var{sigma}. \var{mu} can have any value,
! and \var{sigma} must be greater than zero.
\end{funcdesc}
\begin{funcdesc}{normalvariate}{mu, sigma}
! Normal distribution. \var{mu} is the mean, and \var{sigma} is the
! standard deviation.
\end{funcdesc}
\begin{funcdesc}{vonmisesvariate}{mu, kappa}
! \var{mu} is the mean angle, expressed in radians between 0 and
! 2*\emph{pi}, and \var{kappa} is the concentration parameter, which
! must be greater than or equal to zero. If \var{kappa} is equal to
! zero, this distribution reduces to a uniform random angle over the
! range 0 to 2*\emph{pi}.
\end{funcdesc}
\begin{funcdesc}{paretovariate}{alpha}
! Pareto distribution. \var{alpha} is the shape parameter.
\end{funcdesc}
\begin{funcdesc}{weibullvariate}{alpha, beta}
! Weibull distribution. \var{alpha} is the scale parameter and
! \var{beta} is the shape parameter.
\end{funcdesc}
***************
*** 94,153 ****
\begin{funcdesc}{shuffle}{x\optional{, random}}
! Shuffle the sequence \var{x} in place.
! The optional argument \var{random} is a 0-argument function returning
! a random float in [0.0, 1.0); by default, this is the function
! \function{random()}.
!
! Note that for even rather small \code{len(\var{x})}, the total number
! of permutations of \var{x} is larger than the period of most random
! number generators; this implies that most permutations of a long
! sequence can never be generated.
\end{funcdesc}
\begin{seealso}
! \seemodule{whrandom}{The standard Python random number generator.}
\end{seealso}
-
-
- \subsection{The Random Number Generator Interface
- \label{rng-objects}}
-
- % XXX This *must* be updated before a future release!
-
- The \dfn{Random Number Generator} interface describes the methods
- which are available for all random number generators. This will be
- enhanced in future releases of Python.
-
- In this release of Python, the modules \refmodule{random},
- \refmodule{whrandom}, and instances of the
- \class{whrandom.whrandom} class all conform to this interface.
-
-
- \begin{funcdesc}{choice}{seq}
- Chooses a random element from the non-empty sequence \var{seq} and
- returns it.
- \end{funcdesc}
-
- \begin{funcdesc}{randint}{a, b}
- \deprecated{2.0}{Use \function{randrange()} instead.}
- Returns a random integer \var{N} such that
- \code{\var{a} <= \var{N} <= \var{b}}.
- \end{funcdesc}
-
- \begin{funcdesc}{random}{}
- Returns the next random floating point number in the range [0.0
- ... 1.0).
- \end{funcdesc}
-
- \begin{funcdesc}{randrange}{\optional{start,} stop\optional{, step}}
- Return a randomly selected element from \code{range(\var{start},
- \var{stop}, \var{step})}. This is equivalent to
- \code{choice(range(\var{start}, \var{stop}, \var{step}))}.
- \versionadded{1.5.2}
- \end{funcdesc}
-
- \begin{funcdesc}{uniform}{a, b}
- Returns a random real number \var{N} such that
- \code{\var{a} <= \var{N} < \var{b}}.
- \end{funcdesc}
--- 117,134 ----
\begin{funcdesc}{shuffle}{x\optional{, random}}
! Shuffle the sequence \var{x} in place.
! The optional argument \var{random} is a 0-argument function
! returning a random float in [0.0, 1.0); by default, this is the
! function \function{random()}.
!
! Note that for even rather small \code{len(\var{x})}, the total
! number of permutations of \var{x} is larger than the period of most
! random number generators; this implies that most permutations of a
! long sequence can never be generated.
\end{funcdesc}
\begin{seealso}
! \seemodule{whrandom}{The standard Python pseudo-random number
! generator.}
\end{seealso}